Lab course materials for IEMBA 8/9 course "Coding and Artificial Intelligence"

Overview

IEMBA 8/9 - Coding and Artificial Intelligence

Course Banner

Dear IEMBA 8/9 students,

welcome to our IEMBA 8/9 elective course Coding and Artificial Intelligence, taught by Prof. Dr. Damian Borth and Prof. Dr. Barbara Weber. In this course, lectures and hands-on lab courses alternate to provide a better learning experience. Lab course materials for Python programming, Machine Learning und Deep Learning are available in and accessible through this repository.

Please use a laptop computer for the lab courses (not a tablet) to be able to fully participate in the exercises.

Happy Coding!

Your IEMBA teaching team


This table lists all coding lab notebooks and exercise notebooks:

Date Topic Lab Notebook Exercise Notebook Solution Notebook
< Mon, Jan 17 Prerequisite - Binder
Open In Colab
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Mon, Jan 17 Python 101: Jupyter Notebooks and Python Basics Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, morning session Python 102: Numerical Math & Images Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, afternoon session Machine Learning I
(Naive Bayes)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, afternoon session Machine Learning II
(k Nearest-Neighbors)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Wed, Jan 19, morning session Deep Learning I
(Artificial Neural Nets)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Wed, Jan 19, afternoon session Deep Learning II
(Convolutional Neural Nets)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
< TBD Exam Exercise - Binder
Open In Colab
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Owner
Artificial Intelligence & Machine Learning (AI:ML Lab) @ HSG
Deep Learning Research by AIML Team @ HSG
Artificial Intelligence & Machine Learning (AI:ML Lab) @ HSG
The code uses SegFormer for Semantic Segmentation on Drone Dataset.

SegFormer_Segmentation The code uses SegFormer for Semantic Segmentation on Drone Dataset. The details for the SegFormer can be obtained from the foll

Dr. Sander Ali Khowaja 1 May 08, 2022
An exploration of log domain "alternative floating point" for hardware ML/AI accelerators.

This repository contains the SystemVerilog RTL, C++, HLS (Intel FPGA OpenCL to wrap RTL code) and Python needed to reproduce the numerical results in

Facebook Research 373 Dec 31, 2022
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on

THUDM 176 Dec 17, 2022
Jihye Back 520 Jan 04, 2023
Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection

Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection Main requirements torch = 1.0 torchvision = 0.2.0 Python 3 Environm

15 Apr 04, 2022
A Self-Supervised Contrastive Learning Framework for Aspect Detection

AspDecSSCL A Self-Supervised Contrastive Learning Framework for Aspect Detection This repository is a pytorch implementation for the following AAAI'21

Tian Shi 30 Dec 28, 2022
์‹œ๊ฐ ์žฅ์• ์ธ์„ ์œ„ํ•œ ์Šค๋งˆํŠธ ์ง€ํŒก์ด์— ํ™œ์šฉ๋  ๋”ฅ๋Ÿฌ๋‹ ๋ชจ๋ธ (DL Model Repo)

SmartCane-DL-Model Smart Cane using semantic segmentation ์ฐธ๊ณ ํ•œ Github repositoy ๐Ÿ”— https://github.com/JunHyeok96/Road-Segmentation.git ๋ฐ์ดํ„ฐ์…‹ ๐Ÿ”— https://

๋ฐ˜๋“œ์‹œ ์กธ์—…ํ•œ๋‹ค (Team Just Graduate) 4 Dec 03, 2021
Food recognition model using convolutional neural network & computer vision

Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper

Hemanth Chandran 1 Jan 13, 2022
(under submission) Bayesian Integration of a Generative Prior for Image Restoration

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration Authors: Majed El Helou, and Sabine Sรผsstrunk {Note: p

Majed El Helou 22 Dec 17, 2022
Wordle Env: A Daily Word Environment for Reinforcement Learning

Wordle Env: A Daily Word Environment for Reinforcement Learning Setup Steps: git pull [email&#

2 Mar 28, 2022
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19

2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor

LShi 547 Dec 26, 2022
Official code for the paper "Self-Supervised Prototypical Transfer Learning for Few-Shot Classification"

Self-Supervised Prototypical Transfer Learning for Few-Shot Classification This repository contains the reference source code and pre-trained models (

EPFL INDY 44 Nov 04, 2022
UFT - Universal File Transfer With Python

UFT 2.0.0 UFT (Universal File Transfer) is a CLI tool , which can be used to upl

Merwin 1 Feb 18, 2022
Calibrate your listeners! Robust communication-based training for pragmatic speakers. Findings of EMNLP 2021.

Calibrate your listeners! Robust communication-based training for pragmatic speakers Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman Findings of

Rose E. Wang 3 Apr 02, 2022
DrQ-v2: Improved Data-Augmented Reinforcement Learning

DrQ-v2: Improved Data-Augmented RL Agent Method DrQ-v2 is a model-free off-policy algorithm for image-based continuous control. DrQ-v2 builds on DrQ,

Facebook Research 234 Jan 01, 2023
Fuzzing tool (TFuzz): a fuzzing tool based on program transformation

T-Fuzz T-Fuzz consists of 2 components: Fuzzing tool (TFuzz): a fuzzing tool based on program transformation Crash Analyzer (CrashAnalyzer): a tool th

HexHive 244 Nov 09, 2022
D2Go is a toolkit for efficient deep learning

D2Go D2Go is a production ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms. W

Facebook Research 744 Jan 04, 2023
Ludwig Benchmarking Toolkit

Ludwig Benchmarking Toolkit The Ludwig Benchmarking Toolkit is a personalized benchmarking toolkit for running end-to-end benchmark studies across an

HazyResearch 17 Nov 18, 2022
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

Automatic, Readable, Reusable, Extendable Machin is a reinforcement library designed for pytorch. Build status Platform Status Linux Windows Supported

Iffi 348 Dec 24, 2022
IJCAI2020 & IJCV 2020 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo

Seg_Uncertainty In this repo, we provide the code for the two papers, i.e., MRNet๏ผšUnsupervised Scene Adaptation with Memory Regularization in vivo, IJ

Zhedong Zheng 348 Jan 05, 2023